Czech

Not applicable.

Learning outcomes - general competencies:
The skills associated with the use and treatment of information.
The ability of analysis and synthesis, application knowledge in practice, solve problems independently
Industry-specific competencies:
Students understand the principles of data acquisition, gain knowledge of data processing in information systems and their adaptation for presentation.

Knowledge of working with MS Office.

Not applicable.

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Attendance at lectures is not compulsory. Computer-aided exercises are compulsory, attendance is monitored. One of absence from seminars, teacher apologize. Student replace this lack of elaboration specifically assigned homework.
During the semester, written semester test for a maximum of 30 points. For this semester test, there is no retake. If a student is properly documented and teacher excused absence just in lessons, where he writes a midterm exam, you may report it to the alternative.

In the second lecture is given to students separate project for a maximum of 70 points. So this project was recognized for his student must obtain a minimum 20 points. Student submits a project in the credit week.
Students who have Individual Study Plan, ie. They do not go into teaching for the credit must develop and submit a separate stand-alone project.

The course focuses on the principles and methods of data collection and processing in information systems and their adaptation for presentation.

Topics of the lectures:
Character data from various sources, search options
Database tables, attributes, data types
Handling tables and records, views and reports
Working with data in MS Excel
Power Pivot, data analysis tool
Decision support systems
Data aggregation and analysis (OLAP)

The workout is required continuous training, exercises are designed to process jobs based on the source data files and results presentation.

Not applicable.

The aim is understanding the nature of the data from various sources and to gain knowledge allowing them to analyze and process skills, including presentation in an appropriate form for management decision support.
Learning outcomes - general competencies:
The skills associated with the use and treatment of information.
The ability of analysis and synthesis, application knowledge in practice, solve problems independently
Industry-specific competencies:
Students understand the principles of data acquisition, gain knowledge of data processing in information systems and their adaptation for presentation.

Attendance at lectures is not compulsory. Computer-aided exercises are compulsory, attendance is monitored. One of absence from seminars, teacher apologize. Student replace this lack of elaboration specifically assigned homework.

During the semester, written semester test for a maximum of 20 points. For this semester test, there is no retake. If a student is properly documented and teacher excused absence just in lessons, where he writes a midterm exam, you may report it to the alternative.

In the second lecture is given to students separate project for a maximum of 20 points. So this project was recognized for his student must obtain a minimum. 10 points. Student submits a project in the credit week.
Students who have Individual Study Plan, ie. They do not go into teaching for the credit must develop and submit a separate stand-alone project. For this particular project can get max. 30 points.

Not applicable.

Not applicable.

BARILLA, J. Microsoft Excel 2013 :podrobná uživatelská příručka. Brno: Computer Press, 2013. 1. vyd. 496 s. ISBN 978-80-251-4114-4.
KŘÍŽ, J. Zpracování dat. Učební text. VUT v Brně, fakulta podnikatelská.(bude vydáno v září 2015).

CONOLLY, T., C. BEGG a R. HOLOWCZAK. Mistrovství – Databáze : Profesionální průvodce tvorbou efektivních databází. 1.vyd. Brno: Computer Press, 2009. 584 s. ISBN 978-80-251-2328-7.
LACKO, L. Jak vyzrát na SQL Server 2008. Brno: Computer Press, 2009. 469 s. ISBN 978-80-251-2101-6.